1. Technical Field
This invention concerns a process and an apparatus for processing signals. It applies in particular to the processing of signals representative of measurements made on samples to determine similarities between them. More specifically, this invention applies to the signals generated by a chromatograph to determine whether two samples of oil come from reservoirs or layers that are connected.
2. Background Art
The characterization of reservoir continuity provides information aimed at reducing the key uncertainties in an oil field whose exploitation is being contemplated, and at planning and implementing optimum reservoir development. Such characterization is therefore of great interest to the oil industry.
Reservoir characterization and reservoir continuity studies can be achieved in various ways. Some examples of characterization methods aimed at estimating reservoir compartmentalization are PVT (Pressure, Volume, Temperature) measurements, isotope analysis, GCMS (Gas Chromatography—Mass Spectrometry) techniques or FTIR (Fourier Transform Infra Red) spectroscopy, and multidimensional gas chromatography.
Among these methods, the use of oil fingerprints obtained by the analysis of gas chromatograms of crude oil is one of the quickest and least expensive. The oil fingerprint technique is relatively simple to implement. It comprises comparing various gas chromatograms of samples from different wells in an oil field. The differences between the chromatograms are used as indicators to identify possible barriers between the reservoirs covered by these wells.
Since the beginning of the 1980's, this technique, called ROF (Reservoir Oil Fingerprinting), has been widely used to estimate the connections between reservoirs or, what amounts to the same thing, the presence of flow barriers between two reservoirs. The ROF method is based on the comparison of several chromatograms obtained in the same chromatographic conditions. More specifically, it is based on the differences between the peak height ratios of the various samples analyzed.
The two peak heights used to calculate each ratio are generally selected so that they are close to one another to avoid differences due to phenomena other than reservoir compartmentalization, such as evaporation, gravitational gradients, and the immobilization of heavy components in the chromatograph. In effect, the incoherencies introduced by those mechanisms are particularly significant for components having significant retention time differences.
It is generally accepted that the accuracy of chromatographic analysis is on the order of 1 to 3%. Based on that range, differences in peak height ratios of 5 to 10% or even more cannot be attributed to analytical errors and should represent real compositional differences in crude oil composition. It is therefore customary to use a restricted selection of the most discriminating ratios to separate crude oils into meaningful groups. These groups can then be represented on star diagrams that represent the ratios in one plane to facilitate comparison.
However, this technique presents serious limitations, particularly with respect to the uncertainties as to peak height ratios: the repeatability deviations of the analysis conditions and the deterioration of the chromatographic column over time play a decisive role that is not taken into account. Furthermore, the uncertainty as to each ratio is highly dependent upon the chromatographic peaks used in that ratio. Problems such as coelutions (simultaneous detection of different components poorly separated by chromatography) or measurement noise affect the error assigned to each ratio. This problem can lead to erroneous interpretations of the chromatographic data. As proof of this, changing the list of the peak height ratios to be used in a star diagram can lead to very different results.
In addition, since only a restricted number of peak height ratios is considered, the star diagram is only a partial representation of the spatial topology of all of the peak height ratios. Furthermore, slight but numerous differences in composition between samples can have a considerable impact. This compositional variability and the subsequent difficulty of restricting the number of peak height ratios selected can lead to erroneous results.
Other interpretations using GC (Gas Chromatography) peak height ratios in statistical methods are also possible, such as ascending hierarchical classification, principal component analysis, or fuzzy logic classification. However, it is important to note that all those methods are based on relative differences in peak height ratios, the uncertainties of which are undetermined. The results obtained are therefore not expressed in absolute terms and are restricted to the comparison of crude oil samples on scales that are not the same from one series of comparisons to another.
In other words, the current state of the art does not provide a scale on which differences between samples can be universally measured. The experience acquired on past projects is therefore of little use for future projects. This is all the more troubling because there may be slight differences in composition within a single reservoir or reservoirs that are in fact connected (phenomenon of compositional gradients). Because the current state of the art does not allow the amplitudes of those phenomena to be universally quantified, specialists cannot determine whether differences between samples do or do not signify actual permeability barriers between reservoirs.